The clinical diagnosis of glaucoma relies heavily on visual field testing. However, current visual field tests based on simple light detection can yield normal results in the presence of extensive glaucomatous nerve damage. New types of visual field tests are needed that can reliably detect glaucoma at an early stage. The proposed research will address this need with an investigation of pattern discrimination in the normal and the glaucomatous visual field. The project will focus on a new stimulus paradigm in which the subject's task is to detect a patch of organized dots in a surrounding field of randomly arranged dots. The stimuli are presented on a CRT screen under computer control, and the arrangement of dots in the target patch can be varied from completely random to completely regular, or coherent. Specific studies will examine how changes of dot size, target size, dot dynamics, average luminance contrast and target coherence affect the target visibility for normal control subjects, glaucoma suspects and patients with confirmed glaucoma. The long-range goals of the research are to: 1) identify stimulus parameters that optimize the sensitivity and specificity of pattern discrimination testing for glaucoma detection and incorporate these optimal parameters into an efficient protocol for clinical use; 2) determine the relative performance of optimized pattern discrimination tests and standard clinical visual field tests for early detection of glaucoma; 3) understand the relationship between pattern discrimination loss and optic nerve damage in glaucoma.